Project August 2005

Transcription

1 MAINTENANCE QUALITY ASSURANCE SYNTHESIS OF MEASURES Project August 2005 Midwest Regional University Transportation Center College of Engineering Department of Civil and Environmental Engineering University of Wisconsin, Madison Authors: Teresa M. Adams and Janille Smith University of Wisconsin-Madison Principal Investigator: Teresa M. Adams, PhD. Professor, Department of Civil and Environmental Engineering, University of Wisconsin-Madison

2 TECHNICAL REPORT DOCUMENTATION PAGE 1. Report No. 2. Government Accession No. 3. Recipient s Catalog No. CFDA Title and Subtitle Maintenance Quality Assurance - Synthesis of Measures 5. Report Date August Performing Organization Code 7. Author/s Teresa M. Adams and Janille Smith University of Wisconsin-Madison 9. Performing Organization Name and Address Midwest Regional University Transportation Center University of Wisconsin-Madison 1415 Engineering Drive, Madison, WI Sponsoring Organization Name and Address U.S. Department of Transportation Research and Special Programs Administration th Street, SW Washington, DC Performing Organization Report No. MRUTC Work Unit No. (TRAIS) 11. Contract or Grant No. WISDOT Type of Report and Period Covered Final Report 10/04 08/ Sponsoring Agency Code 15. Supplementary Notes Project completed for the Midwest Regional University Transportation Center with support from the Wisconsin Department of Transportation through the Transportation Asset Management Pooled Fund Research Program. 16. Abstract Constrained budgets and reduced funding are causing state transportation agencies to re-evaluate spending and allocations for maintenance. Much attention is being placed on accounting for maintenance expenditures and justifying maintenance budgets. One approach is to relate highway maintenance to highway performance through maintenance quality assurance (MQA). MQA programs help decision-makers understand maintenance conditions, set priorities, and document the relationship between dollars spent and outcomes. There are guidelines available to assist in the creation of MQA programs, but no comprehensive resources on specific quantitative measures for maintenance quality. States that already have programs are interested in communication with others on how programs are used to improve expenditure decision and justify budgets. Additionally, states interested in establishing an MQA program want to know what measures to use and what others are doing. Two critical barriers for establishing and maturing MQA programs are the lack of a commonly understood set of terms for communication about MQA, and a lack of consensus on a set of commonly recognized maintenance features, characteristics and measures of maintenance performance. This report defines the essential terms necessary to discuss the concepts of highway maintenance quality assurance and presents a synthesis of the measures for maintenance quality assurance used by 26 state transportation agencies. It is expected that common terms and measures will enable agencies to better evaluate their own programs, the performance of their highways, improve communication among agencies and provide a basis for further development of MQA programs. 17. Key Words Maintenance, Maintenance quality assurance (MQA), performance measures, asset management 19. Security Classification (of this report) Unclassified Form DOT F (8-72) 18. Distribution Statement No restrictions. This report is available through the Transportation Research Information Services of the National Transportation Library. 20. Security Classification (of this page) Unclassified 21. No. Of Pages Price Reproduction of form and completed page is authorized. -0- ii

3 DISCLAIMER This research was funded by the Midwest Regional University Transportation Center through the Transportation Asset Management Pooled Fund Research Program administered by the Wisconsin Department of Transportation and the Federal Highway Administration. The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the U.S. Department of Transportation, University Transportation Centers Program, in the interest of information exchange. The U.S. Government assumes no liability for the contents or use thereof. The contents do not\ necessarily reflect the official views of the Midwest Regional University Transportation Center, the University of Wisconsin, the Wisconsin Department of Transportation or the Federal Highway Administration at the time of publication. The United States Government assumes no liability for its contents or use thereof. This report does not constitute a standard, specification, or regulation. The United States Government does not endorse products or manufacturers. Trade and manufacturers names appear in this report only because they are considered essential to the object of the document. ACKNOWLEDGEMENTS This report is the result of a study funded by the Transportation Asset Management Pooled Fund Research Program in conjunction with the National MQA Peer Exchange held in Madison, Wisconsin in October The program committee for the National MQA Peer Exchange served as the project advisory committee: Alison Lebwohl, Chair, Wisconsin Department of Transportation; Al Bailey, California Department of Transportation; Rico Baroga, Washington State Department of Transportation; Jason Bittner, University of Wisconsin-Madison; Mike Bousliman, Montana Department of Transportation; Jennifer Brandenburg, North Carolina Department of Transportation; James Carney, Missouri Department of Transportation; Celso Gatchalian, Federal Highway Administration; Howard Rosen, University of Wisconsin Madison; Lee Smithson, American Association of State Highway and Transportation Officials; James Sorenson, Federal Highway Administration; and Steve Wilcox, New York Department of Transportation. In addition, the authors acknowledge contributions by Frank Richards, Alaska Department of Transportation. iii

4 Table of Contents MAINTENANCE QUALITY ASSURANCE SYNTHESIS OF MEASURES... i DISCLAIMER... iii ACKNOWLEDGEMENTS... iii TECHNICAL REPORT DOCUMENTATION PAGE... ii EXECUTIVE SUMMARY... vi 1 INTRODUCTION Objectives Methodology Related Studies Organization of this Report MQA TERMINOLOGY MAINTENANCE CATEGORIES, CHARACTERISTICS, AND FEATURES Roadway Drainage Roadside and Vegetation Traffic Management Snow and Ice Bridges Rest Areas MEASURES FOR MQA RELATIONSHIP TO SCOTTSDALE WORKSHOP FINDINGS DISCUSSION AND CONCLUSIONS RECOMMENDATIONS REFERENCES iv

5 Table of Tables Table 1. Summary of Inventory Results... 8 Table 2. Inventory of Characteristics for Flexible and Rigid Roadway Pavement Feature Table 3. Inventory of Characteristics for Shoulder Roadway Features Table 4. Inventory of Drainage Features Table 5. Inventory of Roadside and Vegetation Features Table 6. Inventory for Traffic Management Features Table 7. Inventory of Snow and Ice Features Table 8: Inventory of Bridge Features Table 9. Inventory of Rest Area Features Table 10. Measures for Roadway Flexible Pavement Maintenance Quality Table 11. Measures for Roadway Rigid Pavement Maintenance Quality Table 12. Measures for Roadway Shoulder Maintenance Quality Table 13. Measures for Drainage Maintenance Quality Table 14. Measures for Traffic Management Maintenance Quality Table 15. Measures for Roadside and Vegetation Maintenance Quality Table 16. Measures for Snow and Ice Maintenance Quality Table 17. Measures for Bridge Maintenance Quality Table 18. Measures for Rest Areas Maintenance Quality Table 19. Reinterpretation of Scottsdale Workshop Findings Table of Figures Figure 1. Relationship between Category, Feature and Characteristic... 6 Figure 2.Common Flexible Pavement Characteristics Figure 3. Common Rigid Pavement Characteristics Figure 4. Common Shoulder Characteristics Figure 5. Common Drainage Features Figure 6. Common Roadside and Vegetation Feature Figure 7. Common Traffic Management Features Figure 8. Common Snow and Ice Features Figure 9. Common Bridge Feature Figure 10. Common Rest Area Features v

6 EXECUTIVE SUMMARY Constrained budgets and reduced funding have caused states to re-evaluate spending and allocations for maintenance. Much attention is being placed on accounting for maintenance expenditures and justifying maintenance budgets. One approach is to relate highway maintenance to highway performance through maintenance quality assurance (MQA). MQA programs help decision-makers to understand maintenance conditions, set priorities, and to document the relationship between dollars and outcomes. This report provides a synthesis of the measures for maintenance condition as used in maintenance quality assurance programs. The goals of this report are to provide a comprehensive list of measures used to quantify maintenance performance, and to highlight needs and next steps in the development of MQA programs. The development of MQA programs comes in the midst of a national shift towards using measures to manage government. States practicing MQA want to know what other states are doing, what measures are being used, and what works. It is the expectation that a common understanding of MQA and measures will enable states to better evaluate their own programs, the performance of their highways, and improve state-to-state communication about MQA program development and the effectiveness of maintenance strategies. This report is the result of a study funded by the Transportation Asset Management Pooled Fund Research Program. The study was completed in conjunction with the National MQA Peer Exchange held in Madison, Wisconsin in October 2004, and co-hosted by the Wisconsin DOT (WisDOT) and the Midwest Regional University Transportation Center (MRUTC) at the University of Wisconsin-Madison. The study began in December 2004 and concluded in August Representatives from the sponsoring states and the program committee for the National MQA Peer Exchange served as the advisory project committee. The MQA Documents and Materials Library ( was the primary source of information about MQA programs at state transportation agencies. The website has a comprehensive collection of field guides, rating manuals, reports, and field checklists that were submitted by many of the agencies that participated in the National Maintenance Quality Assurance Peer Exchange. Thirty-three transportation agencies including two Canadian provinces submitted documents to the library. The website is being updated and maintained by the MRUTC as agencies submit new documents. The contents of this report are limited to information available in December The study accomplished two main objectives. The first was to assemble of set of common measures for maintenance quality by reviewing and synthesizing the measures used by individual agencies. The second objective was to evaluate consensus and evolution of maintenance quality measurement since the National Workshop on Commonly Recognized Measures for Maintenance held in Scottsdale Arizona in As the work progressed it became clear that agencies use different and sometimes conflicting terms to describe aspects of their MQA programs. To facilitate communication and development of MQA program concepts and analysis, this report presents and defines a set of essential terms for MQA. The terms refine, extend and are consistent with terms defined in the glossary of the NCHRP Report 422 Maintenance QA Program Implementation Manual. The MQA terms vi

7 presented herein are the key scholarly contribution of this research effort. Clear and commonly understood definitions of terms like feature, characteristic, standard, measure, threshold, and target are essential for effective communication. The process for identifying measures involved several steps. The first was to identify maintenance categories logical groups of maintenance features based on their location or function along a highway. The second was to assemble an inventory of maintenance features physical assets or activities whose condition is measured in the field, and maintenance characteristics specific qualities/defects in a maintenance feature that are condition evaluated. In the third step, similar categories, features, and characteristics with different names were combined. Finally, measures and standards were identified for each feature and characteristic. Overall states use very similar categories for organizing maintenance features and characteristics but not enough agreement exists on features and characteristics to allow for the identification of a set of common measures for each category. The reason for good agreement on maintenance categories (e.g. roadway, drainage, traffic management and bridges etc.) is that they are tied to maintenance budgeting and work activities. There is little agreement among the states on what particular features or characteristics are important to measure in each category. When compared to results of Scottsdale meeting in 2000, MQA programs have evolved considerably. MQA is becoming a recognized business function at state transportation agencies. Terminology for MQA analysis and business has evolved significantly but no standard exists. It is expected that the findings of this report will have far reaching implications in the area of highway maintenance. An agency beginning a program could use this to design measures; for agencies with established programs, this information can be used to expand their program to include new measures or to improve existing measures or to eliminate measures. The broader maintenance community can ultimately use these findings to launch the discussion about developing consensus on and adopting a set of common measures for MQA. This report is available online at the MRUTC website ( Notification of the report s availability was disseminated to the participants of the MQA Peer Exchange via . The report was submitted to the AASHTO Transportation Asset Management Today website ( vii

8 1 INTRODUCTION Constrained budgets and reduced funding have caused states to re-evaluate spending and allocations for maintenance. Much attention is being placed on accounting for maintenance expenditures and justifying maintenance budgets. One approach is to relate highway maintenance to highway performance through maintenance quality assurance (MQA). The idea of quality in maintenance was first considered in the 1960 s as a part of a maintenance management system concept (1). The notion of quality in highway maintenance has gained momentum in recent years as the national focus shifts from infrastructure design and construction to maintenance and rehabilitation (2). Performance measures are now being used in transportation maintenance to ensure quality, as is being done in other transportation fields such as transportation planning (3). MQA is a process that uses quantitative quality indicators to assess the performance of maintenance programs. These programs are outcome based and provide statistically valid, reliable and repeatable measures of asset condition (4) Performance measures are at the foundation of an effective MQA program (5). As the national focus shifts towards using measures to manage government, states are becoming increasingly interested in establishing MQA programs for a combination of reasons. The motivating drivers include legislative mandates, increased accountability, and improved maintenance program management. MQA data are being used for condition assessment, maintenance policy analysis, efficiency measurement, and/or maintenance funds allocation (6). Additional expectations from MQA programs are the detection of insufficient maintenance efforts, poor material performance, and incorrect maintenance procedures (1). There are guidelines available to assist in the creation of MQA programs (1), but less on quantitative measures. States that already have programs are interested in communication with others on how programs are used to increase accountability and budget justification. Additionally, states interested in establishing an MQA program want to know what measures to use and what others are doing. Two critical barriers for establishing and maturing MQA programs are the lack of a commonly understood set of terms for communication about MQA, and a lack of consensus on a set of commonly recognized maintenance features, characteristics and measures of maintenance performance. It is expected that common terms and measures will enable agencies to better evaluate their own programs, the performance of their highways, improve communication among agencies and provide a basis for further development of MQA programs. This report is the result of a study funded by the Transportation Asset Management Pooled Fund Research Program and associated with the National MQA Peer Exchange held in Madison, Wisconsin in October 2004 that was co-hosted by the Wisconsin DOT (WisDOT) and the Midwest Regional University Transportation Center (MRUTC) at the University of Wisconsin- Madison. The study began in December 2004 and concluded in August Representatives from the sponsoring states and the program committee for the National MQA Peer Exchange served as the advisory project committee. The MQA Documents and Materials Library ( was the primary source of information about MQA programs at state transportation agencies. The 1

9 website has a comprehensive collection of field guides, rating manuals, reports, and field checklists that were submitted by many of the agencies that participated in the National Maintenance Quality Assurance Peer Exchange. Thirty-three transportation agencies including two Canadian provinces submitted documents to the library. The website is being updated and maintained by the MRUTC as agencies submit new documents. The contents of this report are limited to information available in December Objectives This report provides a synthesis of the measures used to quantify maintenance condition. The goals are to provide a comprehensive list of measures for quantifying maintenance performance, to present a set of essential terms for communicating about MQA measures, and to identify needs and next steps in the development of MQA programs. In addition, this report presents an evaluation of consensus and evolution of maintenance quality measurement since the National Workshop on Commonly Recognized Measures for Maintenance in Scottsdale Arizona held in Methodology The process for identifying measures for MQA involved several steps. The first step required that MQA programs at state transportation agencies be identified. Documents from 33 transportation agencies including 2 Canadian provinces were used to identify 26 agencies with MQA programs. The second step was to compile an inventory of the maintenance categories, features and characteristics that are measured by each agency. Maintenance categories are logical groups of maintenance features and characteristics based on their location or function along a highway. Maintenance features are the physical assets or activities whose condition is measured in the field, and maintenance characteristics are the specific qualities/defects in a maintenance feature that are condition evaluated. In the third step, similar categories, features, and characteristics with different names were combined. This step involved human judgment to match-up or distinguish between the words used to name the categories, features and characteristics in each agency s program. The descriptions and definitions in the agency s MQA documents were used in this step. From the inventory of the maintenance categories, seven maintenance categories were identified as most frequently used to group maintenance features and characteristics. An inventory of maintenance features and characteristics was used to identify which are most frequently measured by agencies. In the fourth step, measures and standards were identified for the features and characteristics in each maintenance category. The measures and standards reported are for the features and characteristics for which measures could be found in the state documents. Finally, the categories, features, characteristics and measures compiled from the state agencies are compared to the ones identified in 2000 during the National Workshop on Commonly Recognized Measures for Maintenance held in Scottsdale, Arizona. The purpose of the comparison is to evaluate consensus among states and the evolution of MQA measures. 2

10 1.3 Related Studies Several National Cooperative Highway Research Program (NCHRP) studies focus on related aspects of MQA. These studies focus on the use of performance based decision making throughout the transportation industry, the development of maintenance quality assurance programs nationally, and benchmarking initiatives for MQA programs. NCHRP Project 8-32(2): Multimodal Transportation: Development of a Performance-Based Planning Process developed a framework for performance-based transportation planning. The framework provides guidance in the identification and selection of performance measures. The results of this project are available in NCHRP Report 446: A Guidebook for Performance-Based Transportation Planning (7). NCHRP Project 14-12: Highway Maintenance Quality Assurance created an implementation manual that contains guidance for highway agencies on how to develop and implement an MQA program. The results of this project can be found in NCHRP Report 422: Maintenance Quality Assurance Program Implementation Manual (1), and in NCHRP Web Document 8, NCHRP Project 14-13: Customer Driven Benchmarking for Highway Maintenance Activities recognizes that continuous improvement in maintenance management is achieved by providing guidance for the establishment of levels of service or threshold values for acceptable condition of the highway system and its components. This study addresses guidelines for the establishment of benchmarks. The results of this project are published in NCHRP Report 511: The Guide and Primer for Customer Driven Benchmarking of Maintenance Activities (5) and in NCHRP Web Document 58, This report builds upon results of two National MQA conferences. The National Workshop on Commonly Recognized Measures for Maintenance held in Scottsdale, Arizona, 2000 is the first known effort to identify commonly used measures for MQA. The Scottsdale workshop (8) set the stage for commonly used measures by promoting the development of maintenance quality assurance programs and spurring the exchange of information on the process. The National MQA Peer Exchange held in Madison, Wisconsin in October 2004 brought transportation officials together to share information and ideas of current MQA programs and practices and to define a national agenda for MQA program development (4). The identification of common measures for MQA was identified in the Peer Exchange s national agenda. In addition, a conference held in Whitefish, Montana is mentioned frequently in the content of MQA program development however conference materials or proceedings are not publicly available. A survey conducted prior to the Madison MQA peer exchange also revealed a clear need for further research focused on performance measures (6). Survey responses were received from 36/50 states, and 3 of 10 Canadian Provinces. Another related survey conducted by the American Association of State Highway and Transportation Officials (AASHTO) on Performance Measure is relevant to this study. The AASHTO Survey (9) was issued in 2002 with the goal of identifying common measures to facilitate benchmarking, asset management and the development of measurement equipment. Many states are thinking beyond what data to gather; they are concentrating on using information in decision-making. MQA programs include statistical analysis, and states are experimenting 3

11 with alternate reporting formats to effectively communicate to legislatures and the public. States are interested in guidance for selecting sample sections, data integration between maintenance management and other systems, and the incorporation of winter maintenance in an MQA framework (10) (11), (12). Microsoft Excel workbooks are now being used in MQA to provide low-risk and high-performance products for use by DOTs (12). In addition, some MQA programs incorporate information to quantify the agency s performance on environmental stewardship (13). 1.4 Organization of this Report As the work progressed following the research steps described in Section 1.2, it became clear that agencies use different and sometime conflicting terms to describe aspects of their MQA programs. To facilitate communication and development of MQA program concepts and analysis, Chapter 2 presents and defines a set of essential terms for MQA. The terms refine, extend and are consistent with terms defined in the glossary of the NCHRP Report 422 Maintenance QA Program Implementation Manual. Clear and commonly understood definitions of terms like feature, characteristic, standard, measure, threshold, and target are essential for effective communication. The other chapters in this report present results of research steps discussed in Section 1.2. Chapter 3 provides an indication of the states practicing MQA along with a detailed analysis of what is being measured. This chapter lists the categories, features and characteristics being measured in each agency s program. In addition, charts for each category indicate the frequency that features and characteristic are included in the MQA program. Chapter 4 presents the actual measures that states use in the field to assess maintenance condition. The key findings of Chapter 4 are tabulated and presented in tables that provide a comprehensive resource on the current state of practice. Chapter 5 of this report compares the findings in Chapters 3 and 4 to the results and outcomes of the National Workshop on Commonly Recognized Measures for Maintenance. The chapter includes a discussion on the progress and evolution of MQA terminology and measures since the Scottsdale Workshop in Chapter 6 presents the findings and conclusions of this study. The chapter provides an overall picture of the state of practice and the common themes identified from program to program. Chapter 7 provides recommendations for nest steps in the development of MQA concepts, programs and analysis. 4

12 2 MQA TERMINOLOGY Based on review of individual agency documents, the terms used in the business of MQA are diverse and sometimes inconsistent. Many agencies use their own set of terms that are often poorly defined. Furthermore, among agencies, the same term is used to describe subtle but importantly different concepts. A lack of consensus on terminology makes it difficult for maintenance officials to communicate with themselves and with those outside the maintenance profession. A set of terms for MQA were identified as part of NCHRP Project (1). Some agencies have adopted those terms and the definitions in the NCHRP report provide an excellent basis for further development of a terminology for describing the artifacts and concepts of maintenance quality assurance. The following are a proposed set of terms and definitions for MQA. The definitions are consistent with yet refine and expand upon the definitions presented in the glossary of the NCHRP report on Highway MQA (1). In addition, the list includes definitions for terms like threshold and target that were not included in the NCHRP glossary. These definitions reflect the meaning of the terms used in this paper. 1) Maintenance category - A maintenance category is a logical grouping of maintenance features based on their location or function along a highway. Examples include roadway, drainage and traffic management. Categories are made up of features whose condition is measured with respect to a particular characteristic. 2) Maintenance feature - A maintenance feature is a physical asset or activity whose condition is measured in the field. There is one or more maintenance feature in each category. Collectively the maintenance features describe the maintenance quality of a maintenance category. 3) Maintenance characteristic A specific quality/defect in a maintenance feature that is condition evaluated (example: signs can be evaluated with respect to retroreflectivity, appearance, sign height and other characteristics/deficiencies). 4) Standards - A tolerance level or criterion that helps to identify when a feature is not functioning as intended ; a tolerance level or criterion that helps to identify whether a characteristic requires maintenance attention or a characteristic s condition is unacceptable. A standard indicates when maintenance is needed. 5) Measures Measures describe how to quantify the deficiency of a maintenance feature or characteristic. For example linear feet, percentage area, amount of deficiency. 6) Thresholds Thresholds are predetermined system-wide maintenance levels for features and categories. Thresholds can be thought of as a grading scale or LOS indicator for MQA. Thresholds indicate how much or what percentage of the system is with or without deficiency. Thresholds also relate measures to customer satisfaction. 7) Targets Targets relate thresholds to the maintenance budget. The target represents the expected threshold level that is attainable given the budget. 5

13 Figure 1 illustrates the hierarchical relationship between category, feature, and characteristic. A category is a group of related features. There are one or more characteristics for each feature. The distinction between feature and characteristic is important; features are physical assets while characteristics are the physical qualities or defects of the assets. Measures for maintenance quality are concerned with the physical quality of the assets. Yet maintenance quality measures tend to be defined for the feature. One must read the description of the measure to identify the particular characteristic of the feature that is being evaluated. The exception is for flexible pavement, rigid pavements and shoulder features. For these features agencies explicitly identify a set of characteristics and the corresponding measure for each. Figure 1. Relationship between Category, Feature and Characteristic For flexible pavements, rigid pavements and shoulder features. Extensive condition assessment databases already exist. Agencies tend to take advantage of existing inventory and condition assessment databases for MQA. When these databases exist agencies tend to use the available condition information for multiple characteristics to assess the maintenance quality of a feature. For most features, inventory and condition data do not exist. It is thus necessary to collect data in order to assess maintenance quality. Agencies tend to use a random sampling strategy to collect data in the field. To minimize the workload agencies try to identify a single key measure for each feature. 6

14 3 MAINTENANCE CATEGORIES, CHARACTERISTICS, AND FEATURES This chapter presents a snapshot of the maintenance categories, features, and characteristics included in MQA programs and the states that measure them. Specifically, the chapter presents: The maintenance categories most often used to group features and characteristics; The maintenance features and characteristics most often measured; The features and characteristics for which measures could be identified; and Details on who is measuring what, and what is being measured by whom. The chapter draws from MQA program materials available on the MQA documents library. Particularly useful are the rating manuals, reports, and field checklists from 26 agencies. The results of this inventory are solely based on the documents submitted to the MQA Library. Other agencies may have MQA programs and the agencies listed herein may measure other features or characteristics. Before a list of commonly used measures can be assembled it is important to identify what is measured. A maintenance inventory was completed to provide a better understanding of the maintenance categories, features and characteristics being included in MQA programs. Agencies tend to group features and characteristic into maintenance categories which are related to the budget leading to the ability to evaluate budget trade-offs. Seven categories were identified from the agency s documents: 1. Roadway 2. Drainage 3. Traffic management 4. Roadside and vegetation 5. Snow and ice 6. Bridges 7. Rest areas There is good consistency among the agencies regarding the maintenance categories in their MQA programs. The reason for good agreement on maintenance categories (e.g. roadway, drainage, traffic management and bridges, etc.) is that many states use similar maintenance budgeting categories. There is little consistency among states on what particular features or characteristics are important to measure in each category. As a result a large number of features and characteristics were identified. The use of different features and characteristics makes it difficult to identify measures. Some categories are more developed than others as seen by the number of MQA programs including a feature or characteristic and the number of features or characteristics for which measures could be identified. Table 1 provides an overview of each category, showing the largest, smallest and average number of features or characteristics measured in each maintenance category. For example, a minimum of 1, maximum of 7, and average of 3.9 drainage features are measured by state MQA programs. The last column in Table 1 identifies the state MQA programs that measure the largest and second largest number of features/characteristics in a 7

15 category. Traffic management tops the list of most often included categories followed by roadside and vegetation. Table 1. Summary of Inventory Results Category Features/Characteristics States Measuring most Features & Min. Max. Average Characteristics Roadway - Flexible Pavement Iowa and Missouri - Rigid Pavement Missouri and North Carolina - Shoulders Maryland and Missouri Drainage Tennessee and Kansas Traffic Management Colorado, Washington D.C. Mississippi and Missouri Roadside and Vegetation Tennessee, Texas and Wisconsin Snow and Ice Tennessee Bridges Washington D.C. and Missouri Rest Areas California, New York and South Dakota It is important to note that Table 1 counts only the features and characteristics for which measures could be identified. MQA documents include other features and characteristics but without clear indication of the associated measures. The subsections that follow list the characteristics and features in each category. Each category includes five to twenty features or characteristics. Inventory tables, Tables 2 9, show which features or characteristics are measured by each state. Bar charts, Figures 2-10 show the percentage of states that measure each characteristic or feature in a given category. It is important to note that the tables and charts include only the features and characteristics for which measures could be identified. 3.1 Roadway The roadway category consists of three main features flexible pavement, rigid pavement, and shoulders. To evaluate the maintenance quality of these roadway features, agencies tend to define measures for characteristics (quality defects that are condition assessed). These characteristics are measured in the field to determine the overall maintenance condition of each roadway feature. The roadway category is unique in this respect; for all other categories agencies tend to define measures for features. Most, if not all states that assess maintenance quality of pavements use data from their pavement management programs. Consequently, for most states MQA of pavement maintenance is in documents other than those submitted to the MQA Document Library. As a result, not all states provided documents detailing pavement measures to this study. Table 2 lists fourteen flexible pavement characteristics and eleven rigid pavement characteristics identified from ten state MQA programs. The number of flexible pavement characteristics ranges from four to ten; the number of rigid pavement characteristics ranges from three to seven. Missouri and North Carolina lead the way in measuring both the flexible and rigid pavement characteristics. Missouri measures 64% of the flexible pavement characteristics and 64% of the 8

16 rigid pavement characteristics. North Carolina measures 55% of the rigid pavement characteristics. Iowa measures 71% of the flexible pavement characteristics while Texas measures only 29% of the characteristics. Nevada measures only 18% of the rigid pavement characteristics. Figure 2 and Figure 3 show the percentage of states measuring each of the flexible and rigid pavement characteristics. Potholes and cracks are among the most frequently measured characteristics of both the flexible and rigid pavement features. Among the flexible pavement characteristics, rutting is measured by 100% of the MQA programs. Potholes, cracking and surface raveling are each measured in 70% of the MQA programs inventoried, while surface oxidation and longitudinal cracks are only measured in 20% of the programs. Among the rigid pavement characteristics, spall/popouts and joints are each measured in 80% of the MQA programs. Cracking and potholes are measured in 70% and 60% of programs respectively, while rutting, ride quality and longitudinal cracks are only measured in 10% of the programs including rigid pavement. As shown in Table 3, nineteen of the MQA programs measure shoulders characteristics. These programs included one to eight of the ten characteristics listed. Missouri and Maryland each measure 80% of the shoulder characteristics. Wisconsin measures 70%, while Ohio and Mississippi each measure 10% of the shoulder characteristics. Shoulder drop-off was the most frequently measured shoulder characteristic; it is measured in 84% of the MQA programs. As in the flexible and rigid pavement features, cracking and potholes are measured most frequently, 63% and 58% respectively. The least measured shoulder characteristics are shoulder cross slope and vegetation growth. Figure 4 shows the percentage of states measuring each shoulder characteristic. Shoulder dropoff is the most frequently measured shoulder characteristic; 85% of MQA programs measures shoulder drop-off. Portholes and cracking are each measured in approximately 65% of programs while vegetation growth and shoulder cross slope are only measured in approximately 25% of programs. 9

17 Table 2. Inventory of Characteristics for Flexible and Rigid Roadway Pavement Feature State Feature Characteristic CA IA IN KS MD MO NC NE TN TX Alligator Cracks x x x x x Bleeding/Flushing x x x x x x Cracking x x x x x x x Depressions/Bumps x x x x Edge break up (edge raveling) x x x Flexible Roadway Pavement Rigid Roadway Pavement Longitudinal Cracks x x Patching x x x Potholes x x x x x x x Raveling/ Stripping (surface) x x x x x x x Rideability / Ride quality x x x Rutting x x x x x x x x x x Shoving x x x x Surface Oxidation x x Transverse Cracks x x x Cracking x x x x x x x Depressions/Bumps x x x Faulting x x x x x Joints (seal) x x x x x x x x Longitudinal Cracks x Patching x x x Potholes x x x x x x Rideability / Ride quality x Rutting x Spalls/Popouts x x x x x x x x Transverse Cracks x x *AB, CO, DC, KY, MS, NY, OH, SC measure pavement characteristics but do not separate characteristics for flexible and rigid pavements. 10

18 Surface Oxidation Longitudinal Cracks Rideability / Ride quality Patching Transverse Cracks Edge break up (edge raveling) Characteristic Shoving Depressions/Bumps Alligator Cracks Bleeding/Flushing Raveling/ Stripping (surface) Cracking Potholes Rutting 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent of States Inventoried Figure 2.Common Flexible Pavement Characteristics Rideability / Ride quality Longitudinal cracks Rutting Transverse cracks Characteristic Patching Depressions/Bumps Faulting Potholes Cracking Spalls/Popouts Joints (seal) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Percent of States Inventoried Figure 3. Common Rigid Pavement Characteristics 11

19 Table 3. Inventory of Characteristics for Shoulder Roadway Features State or Province AB CA CO IA IN KS KY MD Characteristic Cracking x x x x x x x x x x x x Distortion x x x x x x drainage x x x x x x x x Pavement drop-off to shoulder x x x x x x x x x x Potholes x x x x x x x x x x x x Rutting x x x x x x MO MS NC NE NY OH SC TN TX VA WA WI Shoulder cross slope x x x x x Shoulder drop off to ground x x x x x x x x x x x x x x x x Surface-edge raveling x x x x x x x Vegetation growth x x x x Vegetation growth Shoulder cross slope Rutting Characteristic High shoulder/ Distortion Non-positive drainage Surface-edge raveling Pavement drop-off to shoulder Cracking Potholes Shoulder drop-off to ground Figure 4. Common Shoulder Characteristics 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Percent of States Inventoried 12

20 3.2 Drainage Table 4 lists nine drainage features identified from twenty state MQA programs. The number of drainage features measured by an individual state MQA program ranges from one to seven. Tennessee leads the way in measuring the drainage features, measuring seven out of nine or 78%. Wisconsin and Kansas each measure 67% of the drainage features. Washington D.C., Iowa and Ohio each measure 22% of the drainage features. The Colorado MQA program measures the fewest number of drainage features, measuring 11% of features. Figure 5 shows the percentage of states measuring each of the drainage features. Ditches are the most frequently measured drainage features. Among the drainage features, ditches are measured by 85% of the MQA programs. Curb and gutter, and drop inlets are each measured by 60% of programs. The least measured drainage features are pipes and storm drains, each measured by 20% of programs. 3.3 Roadside and Vegetation Table 5 lists fourteen roadside and vegetation features identified from twenty-one state MQA programs. The number of roadside and vegetation features measured by an individual state MQA program ranges from three to nine. Tennessee, Texas and Wisconsin each measure 64% of the roadside and vegetation features. Missouri measures 47% of features, while Kentucky measures only 21% of the features. Figure 6 shows the percentage of states measuring each of the roadside and vegetation features. Litter/debris is the most frequently measured roadside and vegetation feature. Liter/debris is measured by 76% of state MQA programs. Mowing and fences are each measured by 71% of programs, while brush and tree control is measured by 67% of programs. The least frequently measured features, hazardous debris/roadkill and curb trees/sidewalk edge, are measured by 9% and 14% of programs respectively. 13

21 Table 4. Inventory of Drainage Features State Feature CA CO DC IA IN KS KY MD MO MS MT NC NY OH SC TN UT VA WA WI Catch basins/ Drop inlets x x x x x x x x x x x x Culverts x x x x x x x x x Curb/Gutter x x x x x x x x x x x x Ditches x x x x x x x x x x x x x x x x x Drainage structure x x x x x Pipes x x x x Slope failures/ Washouts x x x x x x x Storm drains x x x x Subsurface drainage x x x x x x x x Table 5. Inventory of Roadside and Vegetation Features State Feature CA CO DC IA IN KS KY MD MO MS MT NC NY OH SC TN TX UT VA WA WI Brush and tree control x x x x x x x x x x x x x x Curb trees /Sidewalk edge x x x Fences x x x x x x x x x x x x x x x Graffiti x x x x x x Hazardous debris/roadkill x x Landscaping x x x x x x x x x Litter/Debris x x x x x x x x x x x x x x x x Litter removal (vegetated areas) x x x x x x x Mowing x x x x x x x x x x x x x x x Noxious weed x x x x x x x x x Retaining walls x x x x Sidewalks/Curb x x x x x x x Slopes x x x x x x x x x x x x x Turf condition x x x x 14

22 Pipes Storm drains Drainage structures Drainage Features Slope failures/washouts Subsurface drainage Culverts Curb and gutter Catch basin/drop inlets Ditches 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Figure 5. Common Drainage Features Percentage of States Inventoried Hazardous debris/roadkill Curb trees/sidewalk edge Turf condition Retaining walls Litter removal (vegetated areas) Roadside and Vegetation Features Graffiti Sidewalks/Curb Landscaping Noxious weed Slopes Mowing Brush and tree control Fences Litter/Debris 0% 10% 20% 30% 40% 50% 60% 70% 80% Figure 6. Common Roadside and Vegetation Feature Percentage of States Inventoried 15

23 3.4 Traffic Management Figure 7 shows the percentage of states measuring each of the traffic management features. Signs are the most frequently measured traffic management features. Signs are measured by 91% of state MQA programs. Guiderail/guardrail and pavement markings are each measured by 82% and 86% of states respectively. IT, object markers and traffic signals are measured by less than 15% of state MQA programs. Table 6 lists fourteen traffic management features identified from twenty-one state MQA programs. The number of traffic management features ranges from one to ten. Colorado, Washington D.C., Missouri and Mississippi lead the way in measuring traffic management features, each measuring 71% of features. Five other state MQA programs measure 64% of traffic management features. Based on the documentation submitted, Washington State measures 21% of features while Minnesota measures 7% of the features. Traffic Management Features ITS Traffic signals Object markers Guard cable Highway lighting Raised pavement markings Barrier walls/ Concrete barriers Delineators Impact attenuators Line striping Pavement markings Guiderail/Guardrail Regulation signs Non-regulation signs 0% 10% Figure 7. Common Traffic Management Features 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage of States Inventoried 16

24 Table 6. Inventory for Traffic Management Features Feature CA Barrier wall/concrete x barriers Delineators Guard cable Guide / x Guard rail Highway lighting Impact x attenuators ITS Systems Line striping x Nonregulation x signs Object markers Pavement x markings Raised pavement x markings Regulation x Signs Traffic Signals State CO DC IA IN KS KY MD MN MO MS MT NC NY OH SC TN TX UT VA WA WI x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x 17

25 3.5 Snow and Ice Table 7 lists three snow and ice features identified from six state MQA programs. The three features identified include hours to bare lane, plowing activity and statewide salt usage. Each state MQA program with the exception of Tennessee measures 33% of the snow and ice features. Tennessee measures 67% of features. Figure 8 shows the percentage of states measuring each snow and ice feature. Hours to bare lane is the most frequently measured feature. Five of six states measure hours to bare lane. 83% of state MQA programs measure hours to bare lane. Table 7. Inventory of Snow and Ice Features State Feature CO MN NC ON TN WI Hours to bare lane x x x x x Plowing activity x Statewide salt usage x Statewide salt usage Snow & Ice Features Plowing activity Hours to bare lane 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Figure 8. Common Snow and Ice Features 3.6 Bridges Percentage of States Inventoried Table 8 lists seven bridge features identified from nine state MQA programs. The number of bridge features measured by a given program ranges from one to four features. Approximately 50% of programs only measure a single feature. The other 50% of states measure three or more features. Figure 9 shows the percentage of states measuring each of the bridge features. Bridge deck and bridge railing are the most frequently measured bridge features; each is measured by 44% of state MQA programs. Painting is only measured in 11% of MQA programs. 18

26 Table 8: Inventory of Bridge Features State Feature DC MS NC NY TN TX UT WA WI Bridge approach x x Bridge deck x x x x Bridge railings x x x x Bridge structure x x Drain holes x x x Joints x x x Painting x Painting Bridge structure Bridge approach Bridge Features Bridge railings Joints Drain holes Bridge deck 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Percentage of States Inventoried Figure 9. Common Bridge Feature 3.7 Rest Areas Table 9 lists five rest area features identified in eight state MQA programs. The number of rest area features measured by a given program ranges from one to five. California, New York and South Dakota, each measure 100% of the rest are features. Colorado measures 80% of the features while the remaining state MQA programs measure fewer than 40% of features. Figure 10 shows the percentage of states measuring each of the rest area features. Parking area is the most frequently measured rest area feature. 88% of states measure parking area. All remaining features are measured in at least 38% of programs, but by no more than 63% of programs. Restroom interior, which is measured in 38% programs, is the least measured feature. 19